Efficient monitoring of network activity in a cloud computing environment

ABSTRACT

System and methods are described for efficient monitoring of network traffic in a public cloud computing environment. In one implementation, a method comprises: generating flow log records of network traffic in the public cloud computing environment; identifying a data packet that presents a potential security risk; identifying a captured data packet (PCAP) record corresponding to the identified data packet; and transmitting the PCAP record to a computing device for network traffic analysis.

COPYRIGHT NOTICE

A portion of the disclosure of this patent document contains materialwhich is subject to copyright protection. The copyright owner has noobjection to the facsimile reproduction by anyone of the patent documentor the patent disclosure, as it appears in the United States Patent andTrademark Office patent file or records, but otherwise reserves allcopyright rights whatsoever.

TECHNICAL FIELD

The present disclosure relates to monitoring of network activity in acomputing environment.

BACKGROUND

“Cloud computing” services provide shared resources, software, andinformation to computers and other devices upon request or on demand.Multi-tenant environments are a type of cloud computing architecturethat often manage large quantities of incoming data from multiplesources and allocate computing resources among numerous users on a dailybasis. In monitoring network activity of multi-tenant environments,current systems typically utilize one of two approaches: metadata-basedmonitoring, where metadata in data packet headers is analyzed, and fullpacket capture monitoring, where the data packet payload is analyzed.While each approach can be used successfully protect against securitythreats with its own advantages and disadvantages, current systemsgenerally utilize one or the other while treating them as mutuallyexclusive approaches.

BRIEF DESCRIPTION OF THE DRAWINGS

The included drawings are for illustrative purposes and serve to provideexamples of possible structures and operations for the disclosedinventive systems, apparatus, methods, and computer-readable storagemedia. These drawings in no way limit any changes in form and detailthat may be made by one skilled in the art without departing from thespirit and scope of the disclosed implementations.

FIG. 1A shows a block diagram of an example environment in which anon-demand database service can be used according to someimplementations.

FIG. 1B shows a block diagram of example implementations of elements ofFIG. 1A and example interconnections between these elements according tosome implementations.

FIG. 2A shows a system diagram of example architectural components of anon-demand database service environment according to someimplementations.

FIG. 2B shows a system diagram further illustrating examplearchitectural components of an on-demand database service environmentaccording to some implementations.

FIG. 3 illustrates a diagrammatic representation of a machine in theexemplary form of a computer system within which one or moreimplementations may be carried out.

FIG. 4 is a block diagram illustrating a cloud computing environmentthat utilizes a conventional approach for monitoring network traffic andperforming network traffic analysis.

FIG. 5 is a block diagram illustrating a cloud computing environmentthat is a variant of the cloud computing environment of FIG. 4.

FIG. 6 is a block diagram illustrating a cloud computing environmentconfigured for efficient network traffic monitoring according to someimplementations.

FIG. 7 is a block diagram illustrating a cloud computing environmentthat is a variant of the cloud computing environment of FIG. 6.

FIG. 8 is a flow diagram illustrating an exemplary method for automatedmonitoring of data packets for potential security risks in a publiccloud computing environment according to some implementations.

DETAILED DESCRIPTION

The implementations described herein relate efficient monitoring ofnetwork activity in a cloud computing architecture (e.g., a multi-tenantenvironment). Specifically, certain implementations relate to a systemfor monitoring network activity that utilizes both metadata analysis andfull packet capture analysis to identify suspicious data packets in apublic cloud. The system identifies information in data packet headersthat is indicative of potential security risks such as, for example, amalicious IP address, and utilizes associated metadata within the datapacket header to perform a targeted lookup of records in which the datapacket has been stored or archived. This approach avoids the need toperform full text searches of all captured data packet records, thusminimizing the amount of data to be downloaded and indexed.

In public cloud environments, most cloud service providers enable thecapture of network packet data on a virtual machine (VM) running intheir corresponding networks, and further provide capabilities to storethe packet data in captured data packet (PCAP) records in their localbinary large object (BLOB) storages. Separately, public cloud providersalso provide the capability to record network flow log information onvirtual private cloud (VPC) based instances in the cloud. In general,when a network forensics or incident responder is tasked withinvestigating a potential security risk, the stored PCAP records areexhaustively analyzed to identify, for example, malicious IP addresses.Further, in order to load terabytes of PCAP records, it is common todeploy a fairly expensive, resource-intensive solution that includesrunning large search clusters, such as Elasticsearch (ES) clusters, inconjunction with tools such as Moloch (which is a large scale, opensource, indexed packet capture and search system) to meet the searchrequirements.

This model is traditionally used in 1P/on-premises environments wherethe network streams are processed through an intrusion detection system(IDS) pipeline, then routed to a Moloch cluster to store the full packetcapture data and then generate network traffic records, for example,using the NetFlow protocol (referred to herein as “NetFlow records”).This approach is resource-intensive but is the only option available in1P environments that scales to the N/S traffic rate requirements in theon-premises datacenters. Deploying a similar capability in a publiccloud environment results in high cost-to-serve (CTS) and faces scalingchallenges due to high traffic rates. If such an infrastructure isdeployed, the incident responder will perform a query to search foroffending IP addresses (potentially from a malicious attacker externalto the network or an insider establishing a connection to a suspicioustarget internet protocol (IP) address) and locate all associated PCAPrecords where the offending IP address is present either as a sender orreceiver.

The implementations described herein address these and otherdisadvantages of current systems by providing a system that leveragesmetadata contained in, or derived from, incoming data packets andfacilitating targeted analysis of PCAP records. Advantages of theimplementations described herein over current systems include, but arenot limited to: (1) generating flow log records for incoming datapackets that include referential links to corresponding PCAP data filesof the incoming data packets, thus facilitating straightforwardlook-ups; (2) performing on-demand targeted retrieval of PCAP recordsfiles rather than performing terabyte-scale searches across the entiretyof a PCAP record repository; and (3) including fingerprint identifiers(e.g., SSL fingerprints) in the flow log records to identify suspiciousdata packets in real-time or shortly thereafter.

As used herein, a “flow log record” refers to a record of network eventsthat includes data fields descriptive of network traffic flow into orout of a network. Flow log records may include identifiers such as, butnot limited to, IP addresses indicative of sources and or destinationsof data, network traffic protocols, data packet sizes, or other suitableinformation. Each record generated may contain data descriptive of aparticular data packet at a metadata level without storing the contentsof the data packet.

Also as used herein, a “captured data packet record” or “PCAP record”refers to data files for storing and archiving data packets received bya network. PCAP records are generally used for network traffic analysis,such as forensic analysis.

Examples of systems, apparatuses, computer-readable storage media, andmethods according to the disclosed implementations are described in thissection. These examples are being provided solely to add context and aidin the understanding of the disclosed implementations. It will thus beapparent to one skilled in the art that the disclosed implementationsmay be practiced without some or all of the specific details provided.In other instances, certain process or method operations, also referredto herein as “blocks,” have not been described in detail in order toavoid unnecessarily obscuring the disclosed implementations. Otherimplementations and applications also are possible, and as such, thefollowing examples should not be taken as definitive or limiting eitherin scope or setting.

In the following detailed description, references are made to theaccompanying drawings, which form a part of the description and in whichare shown, by way of illustration, specific implementations. Althoughthese disclosed implementations are described in sufficient detail toenable one skilled in the art to practice the implementations, it is tobe understood that these examples are not limiting, such that otherimplementations may be used and changes may be made to the disclosedimplementations without departing from their spirit and scope. Forexample, the blocks of the methods shown and described herein are notnecessarily performed in the order indicated in some otherimplementations. Additionally, in some other implementations, thedisclosed methods may include more or fewer blocks than are described.As another example, some blocks described herein as separate blocks maybe combined in some other implementations. Conversely, what may bedescribed herein as a single block may be implemented in multiple blocksin some other implementations. Additionally, the conjunction “or” isintended herein in the inclusive sense where appropriate unlessotherwise indicated; that is, the phrase “A, B, or C” is intended toinclude the possibilities of “A,” “B,” “C,” “A and B,” “B and C,” “A andC,” and “A, B, and C.”

The words “example” or “exemplary” are used herein to mean serving as anexample, instance, or illustration. Any aspect or design describedherein as an “example” or “exemplary” is not necessarily to be construedas preferred or advantageous over other aspects or designs. Rather, useof the words “example” or “exemplary” is intended to present concepts ina concrete fashion.

In addition, the articles “a” and “an” as used herein and in theappended claims should generally be construed to mean “one or more”unless specified otherwise or clear from context to be directed to asingular form. Reference throughout this specification to “animplementation,” “one implementation,” “some implementations,” or“certain implementations” indicates that a particular feature,structure, or characteristic described in connection with theimplementation is included in at least one implementation. Thus, theappearances of the phrase “an implementation,” “one implementation,”“some implementations,” or “certain implementations” in variouslocations throughout this specification are not necessarily allreferring to the same implementation.

Some portions of the detailed description may be presented in terms ofalgorithms and symbolic representations of operations on data bitswithin a computer memory. These algorithmic descriptions andrepresentations are the manner used by those skilled in the dataprocessing arts to most effectively convey the substance of their workto others skilled in the art. An algorithm is herein, and generally,conceived to be a self-consistent sequence of steps leading to a desiredresult. The steps are those requiring physical manipulations of physicalquantities. Usually, though not necessarily, these quantities take theform of electrical or magnetic signals capable of being stored,transferred, combined, compared, or otherwise manipulated. It has provenconvenient at times, principally for reasons of common usage, to referto these signals as bits, values, elements, symbols, characters, terms,numbers, or the like.

It should be borne in mind, however, that all of these and similar termsare to be associated with the appropriate physical quantities and aremerely convenient labels applied to these quantities. Unlessspecifically stated otherwise as apparent from the following discussion,it is appreciated that throughout the description, discussions utilizingterms such as “receiving,” “retrieving,” “transmitting,” “computing,”“generating,” “processing,” “reprocessing,” “adding,” “subtracting,”“multiplying,” “dividing,” “optimizing,” “calibrating,” “detecting,”“performing,” “analyzing,” “determining,” “enabling,” “identifying,”“modifying,” “transforming,” “applying,” “aggregating,” “extracting,”“registering,” “querying,” “populating,” “hydrating,” “updating,”“mapping,” “causing,” “storing,” “prioritizing,” “queuing,” “managing,”“comparing,” “removing,” “assigning,” “correlating,” “selecting,”“capturing,” or the like, refer to the actions and processes of acomputer system, or similar electronic computing device, thatmanipulates and transforms data represented as physical (e.g.,electronic) quantities within the computer system's registers andmemories into other data similarly represented as physical quantitieswithin the computer system memories or registers or other suchinformation storage, transmission, or display devices.

The specific details of the specific aspects of implementationsdisclosed herein may be combined in any suitable manner withoutdeparting from the spirit and scope of the disclosed implementations.However, other implementations may be directed to specificimplementations relating to each individual aspect, or specificcombinations of these individual aspects. Additionally, while thedisclosed examples are often described herein with reference to animplementation in which an on-demand database service environment isimplemented in a system having an application server providing a frontend for an on-demand database service capable of supporting multipletenants, the present implementations are not limited to multi-tenantdatabases or deployment on application servers. Implementations may bepracticed using other database architectures, i.e., ORACLE®, DB2® byIBM, and the like without departing from the scope of theimplementations claimed. Moreover, the implementations are applicable toother systems and environments including, but not limited to,client-server models, mobile technology and devices, wearable devices,and on-demand services.

It should also be understood that some of the disclosed implementationscan be embodied in the form of various types of hardware, software,firmware, or combinations thereof, including in the form of controllogic, and using such hardware or software in a modular or integratedmanner. Other ways or methods are possible using hardware and acombination of hardware and software. Any of the software components orfunctions described in this application can be implemented as softwarecode to be executed by one or more processors using any suitablecomputer language such as, for example, C, C++, Java™ (which is atrademark of Sun Microsystems, Inc.), or Perl using, for example,existing or object-oriented techniques. The software code can be storedas non-transitory instructions on any type of tangible computer-readablestorage medium (referred to herein as a “non-transitorycomputer-readable storage medium”). Examples of suitable media includerandom access memory (RAM), read-only memory (ROM), magnetic media suchas a hard-drive or a floppy disk, or an optical medium such as a compactdisc (CD) or digital versatile disc (DVD), flash memory, and the like,or any combination of such storage or transmission devices.Computer-readable media encoded with the software/program code may bepackaged with a compatible device or provided separately from otherdevices (for example, via Internet download). Any such computer-readablemedium may reside on or within a single computing device or an entirecomputer system, and may be among other computer-readable media within asystem or network. A computer system, or other computing device, mayinclude a monitor, printer, or other suitable display for providing anyof the results mentioned herein to a user.

The disclosure also relates to apparatuses, devices, and systemadapted/configured to perform the operations herein. The apparatuses,devices, and systems may be specially constructed for their requiredpurposes, may be selectively activated or reconfigured by a computerprogram, or some combination thereof.

Example System Overview

FIG. 1A shows a block diagram of an example of an environment 10 inwhich an on-demand database service can be used in accordance with someimplementations. The environment 10 includes user systems 12, a network14, a database system 16 (also referred to herein as a “cloud-basedsystem” or “cloud”), a processor system 17, an application platform 18,a network interface 20, tenant database 22 for storing tenant data 23,system database 24 for storing system data 25, program code 26 forimplementing various functions of the database system 16, and processspace 28 for executing database system processes and tenant-specificprocesses, such as running applications as part of an applicationhosting service. In some other implementations, environment 10 may nothave all of these components or systems, or may have other components orsystems instead of, or in addition to, those listed above.

In some implementations, the environment 10 is an environment in whichan on-demand database service exists. An on-demand database service,such as that which can be implemented using the database system 16, is aservice that is made available to users outside an enterprise (orenterprises) that owns, maintains, or provides access to the databasesystem 16. An “enterprise” refers generally to a company or organizationthat owns one or more data centers that host various services and datasources. A “data center” refers generally to a physical location ofvarious servers, machines, and network components utilized by anenterprise.

As described above, such users generally do not need to be concernedwith building or maintaining the database system 16. Instead, resourcesprovided by the database system 16 may be available for such users' usewhen the users need services provided by the database system 16; thatis, on the demand of the users. Some on-demand database services canstore information from one or more tenants into tables of a commondatabase image to form a multi-tenant database system (MTS). The term“multi-tenant database system” can refer to those systems in whichvarious elements of hardware and software of a database system may beshared by one or more customers or tenants. For example, a givenapplication server may simultaneously process requests for a greatnumber of customers, and a given database table may store rows of datasuch as feed items for a potentially much greater number of customers. Adatabase image can include one or more database objects. A relationaldatabase management system (RDBMS) or the equivalent can execute storageand retrieval of information against the database object(s).

Application platform 18 can be a framework that allows the applicationsof the database system 16 to execute, such as the hardware or softwareinfrastructure of the database system 16. In some implementations, theapplication platform 18 enables the creation, management and executionof one or more applications developed by the provider of the on-demanddatabase service, users accessing the on-demand database service viauser systems 12, or third party application developers accessing theon-demand database service via user systems 12.

In some implementations, the database system 16 implements a web-basedcustomer relationship management (CRM) system. For example, in some suchimplementations, the database system 16 includes application serversconfigured to implement and execute CRM software applications as well asprovide related data, code, forms, renderable web pages, and documentsand other information to and from user systems 12 and to store to, andretrieve from, a database system related data, objects, and Web pagecontent. In some MTS implementations, data for multiple tenants may bestored in the same physical database object in tenant database 22. Insome such implementations, tenant data is arranged in the storagemedium(s) of tenant database 22 so that data of one tenant is keptlogically separate from that of other tenants so that one tenant doesnot have access to another tenant's data, unless such data is expresslyshared. The database system 16 also implements applications other than,or in addition to, a CRM application. For example, the database system16 can provide tenant access to multiple hosted (standard and custom)applications, including a CRM application. User (or third partydeveloper) applications, which may or may not include CRM, may besupported by the application platform 18. The application platform 18manages the creation and storage of the applications into one or moredatabase objects and the execution of the applications in one or morevirtual machines in the process space of the database system 16.

According to some implementations, each database system 16 is configuredto provide web pages, forms, applications, data, and media content touser (client) systems 12 to support the access by user systems 12 astenants of the database system 16. As such, the database system 16provides security mechanisms to keep each tenant's data separate unlessthe data is shared. If more than one MTS is used, they may be located inclose proximity to one another (for example, in a server farm located ina single building or campus), or they may be distributed at locationsremote from one another (for example, one or more servers located incity A and one or more servers located in city B). As used herein, eachMTS could include one or more logically or physically connected serversdistributed locally or across one or more geographic locations.Additionally, the term “server” is meant to refer to a computing deviceor system, including processing hardware and process space(s), anassociated storage medium such as a memory device or database, and, insome instances, a database application, such as an object-orienteddatabase management system (OODBMS) or a relational database managementsystem (RDBMS), as is well known in the art. It should also beunderstood that “server system” and “server” are often usedinterchangeably herein. Similarly, the database objects described hereincan be implemented as part of a single database, a distributed database,a collection of distributed databases, a database with redundant onlineor offline backups or other redundancies, etc., and can include adistributed database or storage network and associated processingintelligence.

The network 14 can be or include any network or combination of networksof systems or devices that communicate with one another. For example,the network 14 can be or include any one or any combination of a localarea network (LAN), wide area network (WAN), telephone network, wirelessnetwork, cellular network, point-to-point network, star network, tokenring network, hub network, or other appropriate configuration. Thenetwork 14 can include a Transfer Control Protocol and Internet Protocol(TCP/IP) network, such as the global internetwork of networks oftenreferred to as the “Internet” (with a capital “I”). The Internet will beused in many of the examples herein. However, it should be understoodthat the networks that the disclosed implementations can use are not solimited, although TCP/IP is a frequently implemented protocol.

The user systems 12 can communicate with the database system 16 usingTCP/IP and, at a higher network level, other common Internet protocolsto communicate, such as the Hyper Text Transfer Protocol (HTTP), HyperText Transfer Protocol Secure (HTTPS), File Transfer Protocol (FTP),Apple File Service (AFS), Wireless Application Protocol (WAP), etc. Inan example where HTTP is used, each user system 12 can include an HTTPclient commonly referred to as a “web browser” or simply a “browser” forsending and receiving HTTP signals to and from an HTTP server of thedatabase system 16. Such an HTTP server can be implemented as the solenetwork interface 20 between the database system 16 and the network 14,but other techniques can be used in addition to or instead of thesetechniques. In some implementations, the network interface 20 betweenthe database system 16 and the network 14 includes load sharingfunctionality, such as round-robin HTTP request distributors to balanceloads and distribute incoming HTTP requests evenly over a number ofservers. In MTS implementations, each of the servers can have access tothe MTS data; however, other alternative configurations may be usedinstead.

The user systems 12 can be implemented as any computing device(s) orother data processing apparatus or systems usable by users to access thedatabase system 16. For example, any of user systems 12 can be a desktopcomputer, a work station, a laptop computer, a tablet computer, ahandheld computing device, a mobile cellular phone (for example, a“smartphone”), or any other Wi-Fi-enabled device, WAP-enabled device, orother computing device capable of interfacing directly or indirectly tothe Internet or other network. When discussed in the context of a user,the terms “user system,” “user device,” and “user computing device” areused interchangeably herein with one another and with the term“computer.” As described above, each user system 12 typically executesan HTTP client, for example, a web browsing (or simply “browsing”)program, such as a web browser based on the WebKit platform, Microsoft'sInternet Explorer browser, Netscape's Navigator browser, Opera'sbrowser, Mozilla's Firefox browser, or a WAP-enabled browser in the caseof a cellular phone, personal digital assistant (PDA), or other wirelessdevice, allowing a user (for example, a subscriber of on-demand servicesprovided by the database system 16) of the user system 12 to access,process, and view information, pages, and applications available to itfrom the database system 16 over the network 14.

Each user system 12 also typically includes one or more user inputdevices, such as a keyboard, a mouse, a trackball, a touch pad, a touchscreen, a pen or stylus, or the like, for interacting with a GUIprovided by the browser on a display (for example, a monitor screen,liquid crystal display (LCD), light-emitting diode (LED) display, etc.)of the user system 12 in conjunction with pages, forms, applications,and other information provided by the database system 16 or othersystems or servers. For example, the user interface device can be usedto access data and applications hosted by database system 16, and toperform searches on stored data, or otherwise allow a user to interactwith various GUI pages that may be presented to a user. As discussedabove, implementations are suitable for use with the Internet, althoughother networks can be used instead of or in addition to the Internet,such as an intranet, an extranet, a virtual private network (VPN), anon-TCP/IP based network, any LAN or WAN or the like.

The users of user systems 12 may differ in their respective capacities,and the capacity of a particular user system 12 can be entirelydetermined by permissions (permission levels) for the current user ofsuch user system. For example, where a salesperson is using a particularuser system 12 to interact with the database system 16, that user systemcan have the capacities allotted to the salesperson. However, while anadministrator is using that user system 12 to interact with the databasesystem 16, that user system can have the capacities allotted to thatadministrator. Where a hierarchical role model is used, users at onepermission level can have access to applications, data, and databaseinformation accessible by a lower permission level user, but may nothave access to certain applications, database information, and dataaccessible by a user at a higher permission level. Thus, different usersgenerally will have different capabilities with regard to accessing andmodifying application and database information, depending on the users'respective security or permission levels (also referred to as“authorizations”).

According to some implementations, each user system 12 and some or allof its components are operator-configurable using applications, such asa browser, including computer code executed using CPU, such as an IntelPentium® processor or the like. Similarly, the database system 16 (andadditional instances of an MTS, where more than one is present) and allof its components can be operator-configurable using application(s)including computer code to run using the processor system 17, which maybe implemented to include a CPU, which may include an Intel Pentium®processor or the like, or multiple CPUs.

The database system 16 includes non-transitory computer-readable storagemedia having instructions stored thereon that are executable by or usedto program a server or other computing system (or collection of suchservers or computing systems) to perform some of the implementation ofprocesses described herein. For example, the program code 26 can includeinstructions for operating and configuring the database system 16 tointercommunicate and to process web pages, applications, and other dataand media content as described herein. In some implementations, theprogram code 26 can be downloadable and stored on a hard disk, but theentire program code, or portions thereof, also can be stored in anyother volatile or non-volatile memory medium or device as is well known,such as a ROM or RAM, or provided on any media capable of storingprogram code, such as any type of rotating media including floppy disks,optical discs, DVDs, CDs, microdrives, magneto-optical discs, magneticor optical cards, nanosystems (including molecular memory integratedcircuits), or any other type of computer-readable medium or devicesuitable for storing instructions or data. Additionally, the entireprogram code, or portions thereof, may be transmitted and downloadedfrom a software source over a transmission medium, for example, over theInternet, or from another server, as is well known, or transmitted overany other existing network connection as is well known (for example,extranet, VPN, LAN, etc.) using any communication medium and protocols(for example, TCP/IP, HTTP, HTTPS, Ethernet, etc.) as are well known. Itwill also be appreciated that computer code for the disclosedimplementations can be realized in any programming language that can beexecuted on a server or other computing system such as, for example, C,C++, HTML, any other markup language, Java™ JavaScript, ActiveX, anyother scripting language, such as VBScript, and many other programminglanguages as are well known.

FIG. 1B shows a block diagram of example implementations of elements ofFIG. 1A and example interconnections between these elements according tosome implementations. That is, FIG. 1B also illustrates environment 10,but FIG. 1B, various elements of the database system 16 and variousinterconnections between such elements are shown with more specificityaccording to some more specific implementations. In someimplementations, the database system 16 may not have the same elementsas those described herein or may have other elements instead of, or inaddition to, those described herein.

In FIG. 1B, the user system 12 includes a processor system 12A, a memorysystem 12B, an input system 12C, and an output system 12D. The processorsystem 12A can include any suitable combination of one or moreprocessors. The memory system 12B can include any suitable combinationof one or more memory devices. The input system 12C can include anysuitable combination of input devices, such as one or more touchscreeninterfaces, keyboards, mice, trackballs, scanners, cameras, orinterfaces to networks. The output system 12D can include any suitablecombination of output devices, such as one or more display devices,printers, or interfaces to networks.

In FIG. 1B, the network interface 20 is implemented as a set of HTTPapplication servers 1001-100N. Each application server 100, alsoreferred to herein as an “app server,” is configured to communicate withtenant database 22 and the tenant data 23 therein, as well as systemdatabase 24 and the system data 25 therein, to serve requests receivedfrom the user systems 12. The tenant data 23 can be divided intoindividual tenant storage spaces 112, which can be physically orlogically arranged or divided. Within each tenant storage space 112,user storage 114, and application metadata 116 can similarly beallocated for each user. For example, a copy of a user's most recentlyused (MRU) items can be stored to user storage 114. Similarly, a copy ofMRU items for an entire organization that is a tenant can be stored totenant storage space 112.

The database system 16 also includes a user interface (UI) 30 and anapplication programming interface (API) 32. The process space 28includes system process space 102, individual tenant process spaces 104and a tenant management process space 110. The application platform 18includes an application setup mechanism 38 that supports applicationdevelopers' creation and management of applications. Such applicationsand others can be saved as metadata into tenant database 22 by saveroutines 36 for execution by subscribers as one or more tenant processspaces 104 managed by tenant management process space 110, for example.Invocations to such applications can be coded using PL/SOQL 34, whichprovides a programming language style interface extension to the API 32.A detailed description of some PL/SOQL language implementations isdiscussed in commonly assigned U.S. Pat. No. 7,730,478, titled METHODAND SYSTEM FOR ALLOWING ACCESS TO DEVELOPED APPLICATIONS VIA AMULTI-TENANT ON-DEMAND DATABASE SERVICE, issued on Jun. 1, 2010, andhereby incorporated by reference herein in its entirety and for allpurposes. Invocations to applications can be detected by one or moresystem processes, which manage retrieving application metadata 116 forthe subscriber making the invocation and executing the metadata as anapplication in a virtual machine.

Each application server 100 can be communicably coupled with tenantdatabase 22 and system database 24, for example, having access to tenantdata 23 and system data 25, respectively, via a different networkconnection. For example, one application server 1001 can be coupled viathe network 14 (for example, the Internet), another application server1002 can be coupled via a direct network link, and another applicationserver 100 _(N) can be coupled by yet a different network connection.Transfer Control Protocol and Internet Protocol (TCP/IP) are examples oftypical protocols that can be used for communicating between applicationservers 100 and the database system 16. However, it will be apparent toone skilled in the art that other transport protocols can be used tooptimize the database system 16 depending on the networkinterconnections used.

In some implementations, each application server 100 is configured tohandle requests for any user associated with any organization that is atenant of the database system 16. Because it can be desirable to be ableto add and remove application servers 100 from the server pool at anytime and for various reasons, in some implementations there is no serveraffinity for a user or organization to a specific application server100. In some such implementations, an interface system implementing aload balancing function (for example, an F5 Big-IP load balancer) iscommunicably coupled between the application servers 100 and the usersystems 12 to distribute requests to the application servers 100. In oneimplementation, the load balancer uses a least-connections algorithm toroute user requests to the application servers 100. Other examples ofload balancing algorithms, such as round robin andobserved-response-time, also can be used. For example, in someinstances, three consecutive requests from the same user could hit threedifferent application servers 100, and three requests from differentusers could hit the same application server 100. In this manner, by wayof example, database system 16 can be a multi-tenant system in whichdatabase system 16 handles storage of, and access to, different objects,data, and applications across disparate users and organizations.

In one example storage use case, one tenant can be a company thatemploys a sales force where each salesperson uses database system 16 tomanage aspects of their sales. A user can maintain contact data, leadsdata, customer follow-up data, performance data, goals and progressdata, etc., all applicable to that user's personal sales process (forexample, in tenant database 22). In an example of a MTS arrangement,because all of the data and the applications to access, view, modify,report, transmit, calculate, etc., can be maintained and accessed by auser system 12 having little more than network access, the user canmanage his or her sales efforts and cycles from any of many differentuser systems. For example, when a salesperson is visiting a customer andthe customer has Internet access in their lobby, the salesperson canobtain critical updates regarding that customer while waiting for thecustomer to arrive in the lobby.

While each user's data can be stored separately from other users' dataregardless of the employers of each user, some data can beorganization-wide data shared or accessible by several users or all ofthe users for a given organization that is a tenant. Thus, there can besome data structures managed by database system 16 that are allocated atthe tenant level while other data structures can be managed at the userlevel. Because an MTS can support multiple tenants including possiblecompetitors, the MTS can have security protocols that keep data,applications, and application use separate. Also, because many tenantsmay opt for access to an MTS rather than maintain their own system,redundancy, up-time, and backup are additional functions that can beimplemented in the MTS. In addition to user-specific data andtenant-specific data, the database system 16 also can maintain systemlevel data usable by multiple tenants or other data. Such system leveldata can include industry reports, news, postings, and the like that aresharable among tenants.

In some implementations, the user systems 12 (which also can be clientsystems) communicate with the application servers 100 to request andupdate system-level and tenant-level data from the database system 16.Such requests and updates can involve sending one or more queries totenant database 22 or system database 24. The database system 16 (forexample, an application server 100 in the database system 16) canautomatically generate one or more SQL statements (for example, one ormore SQL queries) designed to access the desired information. Systemdatabase 24 can generate query plans to access the requested data fromthe database. The term “query plan” generally refers to one or moreoperations used to access information in a database system.

Each database can generally be viewed as a collection of objects, suchas a set of logical tables, containing data fitted into predefined orcustomizable categories. A “table” is one representation of a dataobject, and may be used herein to simplify the conceptual description ofobjects and custom objects according to some implementations. It shouldbe understood that “table” and “object” may be used interchangeablyherein. Each table generally contains one or more data categorieslogically arranged as columns or fields in a viewable schema. Each rowor element of a table can contain an instance of data for each categorydefined by the fields. For example, a CRM database can include a tablethat describes a customer with fields for basic contact information suchas name, address, phone number, fax number, etc. Another table candescribe a purchase order, including fields for information such ascustomer, product, sale price, date, etc. In some MTS implementations,standard entity tables can be provided for use by all tenants. For CRMdatabase applications, such standard entities can include tables forcase, account, contact, lead, and opportunity data objects, eachcontaining pre-defined fields. As used herein, the term “entity” alsomay be used interchangeably with “object” and “table.”

In some MTS implementations, tenants are allowed to create and storecustom objects, or may be allowed to customize standard entities orobjects, for example by creating custom fields for standard objects,including custom index fields. Commonly assigned U.S. Pat. No.7,779,039, titled CUSTOM ENTITIES AND FIELDS IN A MULTI-TENANT DATABASESYSTEM, issued on Aug. 17, 2010, and hereby incorporated by referenceherein in its entirety and for all purposes, teaches systems and methodsfor creating custom objects as well as customizing standard objects in amulti-tenant database system. In some implementations, for example, allcustom entity data rows are stored in a single multi-tenant physicaltable, which may contain multiple logical tables per organization. It istransparent to customers that their multiple “tables” are in fact storedin one large table or that their data may be stored in the same table asthe data of other customers.

FIG. 2A shows a system diagram illustrating example architecturalcomponents of an on-demand database service environment 200 according tosome implementations. A client machine communicably connected with thecloud 204, generally referring to one or more networks in combination,as described herein, can communicate with the on-demand database serviceenvironment 200 via one or more edge routers 208 and 212. A clientmachine can be any of the examples of user systems 12 described above.The edge routers can communicate with one or more core switches 220 and224 through a firewall 216. The core switches can communicate with aload balancer 228, which can distribute server load over different pods,such as the pods 240 and 244. The pods 240 and 244, which can eachinclude one or more servers or other computing resources, can performdata processing and other operations used to provide on-demand services.Communication with the pods can be conducted via pod switches 232 and236. Components of the on-demand database service environment cancommunicate with database storage 256 through a database firewall 248and a database switch 252.

As shown in FIGS. 2A and 2B, accessing an on-demand database serviceenvironment can involve communications transmitted among a variety ofdifferent hardware or software components. Further, the on-demanddatabase service environment 200 is a simplified representation of anactual on-demand database service environment. For example, while onlyone or two devices of each type are shown in FIGS. 2A and 2B, someimplementations of an on-demand database service environment can includeanywhere from one to several devices of each type. Also, the on-demanddatabase service environment need not include each device shown in FIGS.2A and 2B, or can include additional devices not shown in FIGS. 2A and2B.

Additionally, it should be appreciated that one or more of the devicesin the on-demand database service environment 200 can be implemented onthe same physical device or on different hardware. Some devices can beimplemented using hardware or a combination of hardware and software.Thus, terms such as “data processing apparatus,” “machine,” “server,”“device,” and “processing device” as used herein are not limited to asingle hardware device; rather, references to these terms can includeany suitable combination of hardware and software configured to providethe described functionality.

The cloud 204 is intended to refer to a data network or multiple datanetworks, often including the Internet. Client machines communicablyconnected with the cloud 204 can communicate with other components ofthe on-demand database service environment 200 to access servicesprovided by the on-demand database service environment. For example,client machines can access the on-demand database service environment toretrieve, store, edit, or process information. In some implementations,the edge routers 208 and 212 route packets between the cloud 204 andother components of the on-demand database service environment 200. Forexample, the edge routers 208 and 212 can employ the Border GatewayProtocol (BGP). The BGP is the core routing protocol of the Internet.The edge routers 208 and 212 can maintain a table of Internet Protocol(IP) networks or ‘prefixes,’ which designate network reachability amongautonomous systems on the Internet.

In some implementations, the firewall 216 can protect the innercomponents of the on-demand database service environment 200 fromInternet traffic. The firewall 216 can block, permit, or deny access tothe inner components of the on-demand database service environment 200based upon a set of rules and other criteria. The firewall 216 can actas one or more of a packet filter, an application gateway, a statefulfilter, a proxy server, or any other type of firewall.

In some implementations, the core switches 220 and 224 are high-capacityswitches that transfer packets within the on-demand database serviceenvironment 200. The core switches 220 and 224 can be configured asnetwork bridges that quickly route data between different componentswithin the on-demand database service environment. In someimplementations, the use of two or more core switches 220 and 224 canprovide redundancy or reduced latency.

In some implementations, the pods 240 and 244 perform the core dataprocessing and service functions provided by the on-demand databaseservice environment. Each pod can include various types of hardware orsoftware computing resources. An example of the pod architecture isdiscussed in greater detail with reference to FIG. 2B. In someimplementations, communication between the pods 240 and 244 is conductedvia the pod switches 232 and 236. The pod switches 232 and 236 canfacilitate communication between the pods 240 and 244 and clientmachines communicably connected with the cloud 204, for example, viacore switches 220 and 224. Also, the pod switches 232 and 236 mayfacilitate communication between the pods 240 and 244 and the databasestorage 256. In some implementations, the load balancer 228 candistribute workload between the pods 240 and 244. Balancing theon-demand service requests between the pods can assist in improving theuse of resources, increasing throughput, reducing response times, orreducing overhead. The load balancer 228 may include multilayer switchesto analyze and forward traffic.

In some implementations, access to the database storage 256 is guardedby a database firewall 248. The database firewall 248 can act as acomputer application firewall operating at the database applicationlayer of a protocol stack. The database firewall 248 can protect thedatabase storage 256 from application attacks such as SQL injection,database rootkits, and unauthorized information disclosure. In someimplementations, the database firewall 248 includes a host using one ormore forms of reverse proxy services to proxy traffic before passing itto a gateway router. The database firewall 248 can inspect the contentsof database traffic and block certain content or database requests. Thedatabase firewall 248 can work on the SQL application level atop theTCP/IP stack, managing applications' connection to the database or SQLmanagement interfaces as well as intercepting and enforcing packetstraveling to or from a database network or application interface.

In some implementations, communication with the database storage 256 isconducted via the database switch 252. The multi-tenant database storage256 can include more than one hardware or software components forhandling database queries. Accordingly, the database switch 252 candirect database queries transmitted by other components of the on-demanddatabase service environment (for example, the pods 240 and 244) to thecorrect components within the database storage 256. In someimplementations, the database storage 256 is an on-demand databasesystem shared by many different organizations as described above withreference to FIGS. 1A and 1B.

FIG. 2B shows a system diagram further illustrating examplearchitectural components of an on-demand database service environmentaccording to some implementations. The pod 244 can be used to renderservices to a user of the on-demand database service environment 200. Insome implementations, each pod includes a variety of servers or othersystems. The pod 244 includes one or more content batch servers 264,content search servers 268, query servers 282, file servers 286, accesscontrol system (ACS) servers 280, batch servers 284, and app servers288. The pod 244 also can include database instances 290, quick filesystems (QFS) 292, and indexers 294. In some implementations, some orall communication between the servers in the pod 244 can be transmittedvia the pod switch 236.

In some implementations, the app servers 288 include a hardware orsoftware framework dedicated to the execution of procedures (forexample, programs, routines, scripts) for supporting the construction ofapplications provided by the on-demand database service environment 200via the pod 244. In some implementations, the hardware or softwareframework of an app server 288 is configured to execute operations ofthe services described herein, including performance of the blocks ofvarious methods or processes described herein. In some alternativeimplementations, two or more app servers 288 can be included andcooperate to perform such methods, or one or more other serversdescribed herein can be configured to perform the disclosed methods.

The content batch servers 264 can handle requests internal to the pod.Some such requests can be long-running or not tied to a particularcustomer. For example, the content batch servers 264 can handle requestsrelated to log mining, cleanup work, and maintenance tasks. The contentsearch servers 268 can provide query and indexer functions. For example,the functions provided by the content search servers 268 can allow usersto search through content stored in the on-demand database serviceenvironment. The file servers 286 can manage requests for informationstored in the file storage 298. The file storage 298 can storeinformation such as documents, images, and BLOBs. By managing requestsfor information using the file servers 286, the image footprint on thedatabase can be reduced. The query servers 282 can be used to retrieveinformation from one or more file systems. For example, the queryservers 282 can receive requests for information from the app servers288 and transmit information queries to the network file systems (NFS)296 located outside the pod.

The pod 244 can share a database instance 290 configured as amulti-tenant environment in which different organizations share accessto the same database. Additionally, services rendered by the pod 244 maycall upon various hardware or software resources. In someimplementations, the ACS servers 280 control access to data, hardwareresources, or software resources. In some implementations, the batchservers 284 process batch jobs, which are used to run tasks at specifiedtimes. For example, the batch servers 284 can transmit instructions toother servers, such as the app servers 288, to trigger the batch jobs.

In some implementations, the QFS 292 is an open source file systemavailable from Sun Microsystems, Inc. The QFS can serve as arapid-access file system for storing and accessing information availablewithin the pod 244. The QFS 292 can support some volume managementcapabilities, allowing many disks to be grouped together into a filesystem. File system metadata can be kept on a separate set of disks,which can be useful for streaming applications where long disk seekscannot be tolerated. Thus, the QFS system can communicate with one ormore content search servers 268 or indexers 294 to identify, retrieve,move, or update data stored in the NFS 296 or other storage systems.

In some implementations, one or more query servers 282 communicate withthe NFS 296 to retrieve or update information stored outside of the pod244. The NFS 296 can allow servers located in the pod 244 to accessinformation to access files over a network in a manner similar to howlocal storage is accessed. In some implementations, queries from thequery servers 282 are transmitted to the NFS 296 via the load balancer228, which can distribute resource requests over various resourcesavailable in the on-demand database service environment. The NFS 296also can communicate with the QFS 292 to update the information storedon the NFS 296 or to provide information to the QFS 292 for use byservers located within the pod 244.

In some implementations, the pod includes one or more database instances290. The database instance 290 can transmit information to the QFS 292.When information is transmitted to the QFS, it can be available for useby servers within the pod 244 without using an additional database call.In some implementations, database information is transmitted to theindexer 294. Indexer 294 can provide an index of information availablein the database instance 290 or QFS 292. The index information can beprovided to the file servers 286 or the QFS 292.

FIG. 3 illustrates a diagrammatic representation of a machine in theexemplary form of a computer system 300 within which a set ofinstructions (e.g., for causing the machine to perform any one or moreof the methodologies discussed herein) may be executed. In alternativeimplementations, the machine may be connected (e.g., networked) to othermachines in a LAN, a WAN, an intranet, an extranet, or the Internet. Themachine may operate in the capacity of a server or a client machine inclient-server network environment, or as a peer machine in apeer-to-peer (or distributed) network environment. The machine may be apersonal computer (PC), a tablet PC, a set-top box (STB), a PDA, acellular telephone, a web appliance, a server, a network router, switchor bridge, or any machine capable of executing a set of instructions(sequential or otherwise) that specify actions to be taken by thatmachine. Further, while only a single machine is illustrated, the term“machine” shall also be taken to include any collection of machines thatindividually or jointly execute a set (or multiple sets) of instructionsto perform any one or more of the methodologies discussed herein. Someor all of the components of the computer system 300 may be utilized byor illustrative of any of the electronic components described herein(e.g., any of the components illustrated in or described with respect toFIGS. 1A, 1B, 2A, and 2B).

The exemplary computer system 300 includes a processing device(processor) 302, a main memory 304 (e.g., ROM, flash memory, dynamicrandom access memory (DRAM) such as synchronous DRAM (SDRAM) or RambusDRAM (RDRAM), etc.), a static memory 306 (e.g., flash memory, staticrandom access memory (SRAM), etc.), and a data storage device 320, whichcommunicate with each other via a bus 310.

Processor 302 represents one or more general-purpose processing devicessuch as a microprocessor, central processing unit, or the like. Moreparticularly, the processor 302 may be a complex instruction setcomputing (CISC) microprocessor, reduced instruction set computing(RISC) microprocessor, very long instruction word (VLIW) microprocessor,or a processor implementing other instruction sets or processorsimplementing a combination of instruction sets. The processor 302 mayalso be one or more special-purpose processing devices such as anapplication specific integrated circuit (ASIC), a field programmablegate array (FPGA), a digital signal processor (DSP), network processor,or the like. The processor 302 is configured to execute instructions 340for performing the operations and steps discussed herein.

The computer system 300 may further include a network interface device308. The computer system 300 also may include a video display unit 312(e.g., a liquid crystal display (LCD), a cathode ray tube (CRT), or atouch screen), an alphanumeric input device 314 (e.g., a keyboard), acursor control device 316 (e.g., a mouse), and a signal generationdevice 322 (e.g., a speaker).

Power device 318 may monitor a power level of a battery used to powerthe computer system 300 or one or more of its components. The powerdevice 318 may provide one or more interfaces to provide an indicationof a power level, a time window remaining prior to shutdown of computersystem 300 or one or more of its components, a power consumption rate,an indicator of whether computer system is utilizing an external powersource or battery power, and other power related information. In someimplementations, indications related to the power device 318 may beaccessible remotely (e.g., accessible to a remote back-up managementmodule via a network connection). In some implementations, a batteryutilized by the power device 318 may be an uninterruptable power supply(UPS) local to or remote from computer system 300. In suchimplementations, the power device 318 may provide information about apower level of the UPS.

The data storage device 320 may include a computer-readable storagemedium 324 (e.g., a non-transitory computer-readable storage medium) onwhich is stored one or more sets of instructions 340 (e.g., software)embodying any one or more of the methodologies or functions describedherein. These instructions 340 may also reside, completely or at leastpartially, within the main memory 304 and/or within the processor 302during execution thereof by the computer system 300, the main memory304, and the processor 302 also constituting computer-readable storagemedia. The instructions 340 may further be transmitted or received overa network 330 (e.g., the network 14) via the network interface device308. While the computer-readable storage medium 324 is shown in anexemplary implementation to be a single medium, it is to be understoodthat the computer-readable storage medium 324 may include a singlemedium or multiple media (e.g., a centralized or distributed database,and/or associated caches and servers) that store the one or more sets ofinstructions 340.

For simplicity of explanation, the methods of this disclosure aredepicted and described as a series of acts. However, acts in accordancewith this disclosure can occur in various orders and/or concurrently,and with other acts not presented and described herein. Furthermore, notall illustrated acts may be required to implement the methods inaccordance with the disclosed subject matter. In addition, those skilledin the art will understand and appreciate that the methods couldalternatively be represented as a series of interrelated states via astate diagram or events. Additionally, it should be appreciated that themethods disclosed in this specification are capable of being stored onan article of manufacture to facilitate transporting and transferringinstructions for performing such methods to computing devices. The term“article of manufacture,” as used herein, is intended to encompass acomputer program accessible from any computer-readable device or storagemedia.

Efficient Network Activity Monitoring

Certain implementations of the present disclosure provide systems andmethods for automated monitoring of data packets for potential securityrisks in a cloud computing environment, such as a public cloudenvironment. The implementations described herein provide a solutionthat leverages a public cloud environment's native data packet capturecapability while enhancing flow logs to build a map between stored PCAPdata and custom flow log records.

Many cloud computing environments, such as such as Amazon Web Services(AWS), utilize VPC flow logs, which allow for IP traffic data going toand from network interfaces to be captured. Flow logs can be used toperform several tasks, including monitoring of network traffic reachingparticular instances within the cloud computing environment andidentifying overly restrictive security rules. Flow log records can becollected outside of the path of the network traffic without adverselyimpacting network performance. Flow log records can contain variousfields (e.g., metadata identifiers) such as, but not limited to,srcaddr, srcport, dstaddr, dstport, protocol, packets, bytes,account-id, and vpc-id.

Certain implementations utilize flow log records that are modified toinclude custom fields for storing additional metadata identifiers(referred to as “custom flow logs” or “custom flow log records”) tofacilitate mapping flow log records to PCAP records as the PCAP recordsare generated and stored. The following example implementations aredescribed with respect to Amazon Web Services (AWS), though it is to beunderstood that other cloud computing environments may be utilized, andthe example implementations described may be generalized to suchenvironments.

Custom flow log generation may be performed through an extract,transform, and load (ETL) process to include, in addition to theaforementioned fields, metadata identifiers for mapping a flow logrecord to a PCAP record via a pcap_location field (e.g., a storageaddress). PCAP records may be stored in an AWS Simple Storage Service(S3) bucket as inventory files. The pcap_location field may be set as apermanent link to the PCAP data in the S3 bucket from which the customflow log is generated. As inventory files are written, newly arriveddata packets are processed using an ETL process. The custom flow logrecords may be stored in a separate S3 bucket that are processed in thebackground using, for example, an AWS Lambda process to generateListObject entries for all custom flow log records.

-   The custom flow logs may now be scanned through a query, for    example, in a Presto cluster of the AWS Amazon Elastic MapReduce    (EMR) service. When an incident responder start investigating a    potential incident, they may be issue a simple Presto query to    search for the custom flow log records containing a suspicious IP    address (source or destination). When the Presto query completes,    the responder will now have access to a distinct list of PCAP    records in S3 returned as part of the response to the query in the    pcap_location custom field.

In certain implementations, the custom flow logs may be further modifiedto include additional fields in the flow logs, such as one or morefingerprint identifiers. In some implementations, a flow log record maybe modified to include a JA3 hash to facilitate hunting SSL/TLS clientsin the public cloud environment. During SSL handshakes, there is a highprobability that malicious data packets will contain maliciousparameters in their SSL headers. Accordingly, malicious JA3 hashfingerprints may be used in certain implementations to identifypotentially malicious data packets based on JA3 has fingerprintsidentified and stored in a database of known threats (e.g., SSLBL).

FIGS. 4-7 depict cloud computing environments as AWS public cloudcomputing environment for illustrative purposes, though it should bereadily understood by those of ordinary skill in the art that theimplementations described herein are compatible with other cloudcomputing environments.

FIG. 4 is a block diagram illustrating a cloud computing environment 400that utilizes a conventional approach for monitoring network traffic andperforming network traffic analysis. The cloud computing environment 400includes instances 410A-410Z and 430, which may be deployed asCrowdStrike Falcon. Each of instances 410A-410Z may be implementedsimilarly, and only the details of instance 410A are shown to avoidcrowding FIG. 4. Within instance 410A, various cloud computing platforms412A-412Z are implemented which may be managed by a load balancer 414.Cloud computing platform 412A may be, for example, a public cloudcomputing platform that is accessible via an internet gateway 416. Cloudcomputing platform 412Z may be, for example, a private cloud computingplatform that is accessible via a private cloud gateway 418. Trafficmirroring 420 may be performed to copy inbound and outbound networktraffic into cloud storage 422 (e.g., an S3 bucket) for security andthreat monitoring purposes. The instance 410A may further utilize amessage queueing service 424 (e.g., Amazon SQS) in conjunction with anintrusion detection system 426 (e.g., Zeek, Suricata, etc.) to monitornetwork traffic stored in the S3 bucket.

The instance 430 may be utilized by computer security incident responseteam (CSIRT) personnel to analyze network traffic for each of instances410A-410Z. Network traffic data is retrieved from cloud storages of theinstances 410A-410Z by a data packet capture and search platform 432,and may be stored locally in hard disk storage as PCAP recordsutilizing, for example, Moloch capture nodes. Moloch is a large-scalepacket capture and search system that is often utilized in connectionwith cloud computing security infrastructures to to store and indexnetwork traffic in standard PCAP record formats. Metadata associatedwith the PCAP records may be inserted into nodes 436A-436Z of a searchAPI 434 (e.g., Elasticsearch) for performing full text searches of PCAPrecords.

The approach used in cloud computing environment 400 for network trafficmonitoring has several disadvantages, including high cost andsignificant hardware requirements. Moreover, a significant amount ofprocessing time is required due to the vast amount of PCAP record datathat needs to be searched in its entirety. Since only a single copy ofthe PCAP records is stored on a hard disk, this reduces the overallavailability of the PCAP record data.

FIG. 5 is a block diagram illustrating a cloud computing environment 500that represents a modification of the cloud computing environment 400.Instances 510A-510Z may be the same as or similar to the instances410A-410Z discussed with respect to the cloud computing environment 400.The instance 530 is similar to the instance 430, except PCAP records arestored in a cloud storage 538 (e.g., an S3 bucket), which significantlyimproves data availability and durability while reducing costs. However,the cloud computing environment 500 still has the drawbacks of the cloudcomputing environment 400 in that significant amounts of time andcomputing resources are required to search the PCAP record data.

FIG. 6 is a block diagram illustrating a cloud computing environment 600in accordance with the implementations of the disclosure. Instances610A-610Z are similar to instances 410A-410Z except that the instances610A-610Z are modified to generate flow log records including customfields as discussed above. For example, the instance 610A generates andstores PCAP records in its cloud storage 422, and then utilizes aprocess 602 to map PCAP records to flow log records by extractingmetadata identifiers from data packet headers. The flow log records arethen stored in cloud storage 632 (e.g., an S3 bucket) of an instance630. A search of the metadata identifiers in the flow log records can beperformed using a query engine 634 (e.g., Presto) to identify suspiciousdata packets based on, for example, known IP addresses that may presenta security risk. In certain implementations, the flow log records aremodified to include a link to stored PCAP records in the cloud storage632. This may be performed by preprocessing data packets to include anaddress in their metadata that refers to the location of thecorresponding stored PCAP records. The data packets may also bepreprocessed to include fingerprint identifiers in their metadata, whichis also included in the corresponding stored PCAP records anddynamically generated flow log records, thus facilitating downstreamsearching.

A separate instance 650 may be utilized and maintained by a securityresponse center that is responsible for monitoring and incident responseacross the cloud computing environment 600. The instance 650 may utilizethe data packet and search platform 432 and the search API 434 toperform targeted searches of the PCAP records stored in the cloudstorages (e.g., S3 buckets) of the instances 610A-610Z. This allows forminimal downloading and indexing of PCAP records, significantly reducingcosts and processing time.

FIG. 7 is a block diagram illustrating a cloud computing environment 700that represents a modification of the cloud computing environment 600.The cloud computing environment 700 is similar to the cloud computingenvironment 600, except that a process 732 for mapping PCAP records toflow log records is performed by instance 730 rather than by instances710A-710Z to facilitate inline flow log generation and PCAP recordanalysis. In some implementations, one or more of the instances 730 or750 may include additional cloud storage for aggregating and storingPCAP records.

Reference is now made to FIG. 8, which is a flow diagram illustrating anexemplary method 800 for automated monitoring of data packets forpotential security risks in a public cloud computing environment. Themethod 800 may be performed by processing logic comprising hardware(e.g., circuitry, dedicated logic, programmable logic, microcode, etc.),software (such as instructions run on a processing device), or acombination thereof. In some implementations, the method 800 may beperformed by one or more processing devices of a database system (e.g.,the database system 16). It is to be understood that theseimplementations are merely exemplary, and that other devices may performsome or all of the functionality described. Moreover, while the method800 is described as being performed by a processing device, it is to beunderstood that more than one processing device may perform theoperations described under control of, for example, a database system.Thus, recitations of “a processing device” or “the processing device”should not be construed as to being limited to a single processingdevice. Similarly, recitations of “a server” or “the server” should notbe construed as being limited to a single server.

Referring to FIG. 8, at block 810, a server (e.g., a processing deviceor one or more processing devices of a server of the database system 16)of a cloud computing environment (e.g., cloud computing environments 600or 700) generates flow log records of network traffic (e.g., usingprocesses 602 or 732). In some implementations, the flow log recordscomprise metadata identifiers descriptive of data packets processed bythe cloud computing environment. In some implementations, the metadataidentifiers comprise, for example, data descriptive of data packet size,IP addresses, time stamps, or other relevant information included in thedata packet as received, derived therefrom, or generated during theprocessing of the data packet.

At block 820, the server identifies, based on the metadata identifiersof the flow log records, a data packet that presents a potentialsecurity risk. In some implementations, for each data packet processedby the cloud computing environment, the server stores in a correspondingflow log record metadata identifiers comprising a fingerprint identifieror an internet protocol (IP) address. In some implementations, toidentify a data packet as one that presents a potential security risk,the server determines whether the fingerprint identifier or IP addresscorresponds to a suspected or previously detected security risk. In someimplementations, the fingerprint identifier comprises a JA3 SSLfingerprint.

At block 830, the server identifies within/retrieves from from a PCAPrecord repository (e.g., cloud storage 422) a PCAP record correspondingto the received data packet based on the metadata identifiersdescriptive of the data packet. In some implementations, for each datapacket processed by the cloud computing environment, the server storesin a corresponding flow log record metadata identifiers comprising anaddress of a corresponding PCAP record of the data packet within thePCAP record repository. The PCAP record may then be identified in andretrieved from the PCAP record repository based on the address.

In some implementations, the server identifies within/retrieves from thePCAP record repository a plurality of PCAP records associated with afingerprint identifier or an IP address based on metadata of flow logrecords that comprises the fingerprint identifier or the IP address.

At block 840, the server transmits the PCAP record or a plurality ofPCAP records to a computing device for network traffic analysis (e.g.,forensic analysis). In some implementations, the server aggregates PCAPrecords from each virtual machine instance (e.g., instances 610A-610Z or710A-710Z) of the cloud computing environment onto one or more harddisks based on metadata identifiers containing data suggestive of apotential security threat. In some implementations, the PCAP record(s)transmitted to the computing device corresponds to less than 1% of allPCAP record data stored in the PCAP record repository.

In the foregoing description, numerous details are set forth. It will beapparent, however, to one of ordinary skill in the art having thebenefit of this disclosure, that the present disclosure may be practicedwithout these specific details. While specific implementations have beendescribed herein, it should be understood that they have been presentedby way of example only, and not limitation. The breadth and scope of thepresent application should not be limited by any of the implementationsdescribed herein, but should be defined only in accordance with thefollowing and later-submitted claims and their equivalents. Indeed,other various implementations of and modifications to the presentdisclosure, in addition to those described herein, will be apparent tothose of ordinary skill in the art from the foregoing description andaccompanying drawings. Thus, such other implementations andmodifications are intended to fall within the scope of the presentdisclosure.

Furthermore, although the present disclosure has been described hereinin the context of a particular implementation in a particularenvironment for a particular purpose, those of ordinary skill in the artwill recognize that its usefulness is not limited thereto and that thepresent disclosure may be beneficially implemented in any number ofenvironments for any number of purposes. Accordingly, the claims setforth below should be construed in view of the full breadth and spiritof the present disclosure as described herein, along with the full scopeof equivalents to which such claims are entitled.

What is claimed is:
 1. A computer-implemented method for automatedmonitoring of data packets for potential security risks in a publiccloud computing environment, comprising: generating, by a server of thepublic cloud computing environment, flow log records of network traffic,the flow log records comprising metadata identifiers descriptive of datapackets processed by the public cloud computing environment;identifying, by the server, a data packet that presents a potentialsecurity risk based on the metadata identifiers; retrieving, by theserver, a captured data packet (PCAP) record from a PCAP recordrepository, the PCAP record corresponding to the identified data packetbased on the metadata identifiers descriptive of the data packet; andtransmitting, from the server, the PCAP record to a computing device fornetwork traffic analysis.
 2. The computer-implemented method of claim 1,wherein generating the log flow records comprises: for each data packetprocessed by the public cloud computing environment, storing in acorresponding flow log record metadata identifiers comprising an addressof a corresponding PCAP record of the data packet within the PCAP recordrepository, wherein the PCAP record is identified within the PCAP recordrepository based on the address.
 3. The computer-implemented method ofclaim 1, wherein generating the flow log records comprises: for eachdata packet processed by the public cloud computing environment, storingin a corresponding flow log record metadata identifiers comprising afingerprint identifier or an internet protocol (IP) address, whereinidentifying a data packet that presents a potential security riskcomprises determining that the fingerprint identifier or IP addresscorresponds to a suspected or previously detected security risk.
 4. Thecomputer-implemented method of claim 3, further comprising: retrieving,from the PCAP record repository, a plurality of PCAP records associatedwith the fingerprint identifier or the IP address based on flow logrecords that comprise the fingerprint identifier or the IP address intheir respective metadata identifiers; and transmitting, from theserver, the plurality of PCAP records to the computing device.
 5. Thecomputer-implemented method of claim 3, wherein the fingerprintidentifier comprises a JA3 SSL fingerprint.
 6. The computer-implementedmethod of claim 1, further comprising: aggregating, based on themetadata identifiers, PCAP records from each virtual machine instance ofthe public cloud computing environment onto one or more hard disks. 7.The computer-implemented method of claim 1, wherein the PCAP recordtransmitted to the computing device corresponds to less than 1% of allPCAP record data stored in the PCAP record repository.
 8. A databasesystem of a public cloud computing environment, the database systemcomprising: a server; and at least one memory device coupled to theserver, the at least one memory device having instructions storedthereon that, in response to execution by one or more processing devicesof the server, cause the server to: generate flow log records of networktraffic, the flow log records comprising metadata identifiersdescriptive of data packets processed by the public cloud computingenvironment; identify a data packet that presents a potential securityrisk based on the metadata identifiers; retrieve a captured data packet(PCAP) record from a PCAP record repository, the PCAP recordcorresponding to the identified data packet based on the metadataidentifiers descriptive of the data packet; and transmit the PCAP recordto a computing device for network traffic analysis.
 9. The databasesystem of claim 8, wherein to generate the flow log records, the serveris to further: store in a corresponding flow log record, for each datapacket processed by the public cloud computing environment, metadataidentifiers comprising an address of a corresponding PCAP record of thedata packet within the PCAP record repository, wherein the PCAP recordis identified within the PCAP record repository based on the address.10. The database system of claim 8, wherein to generate the flow logrecords, the server is to further: store in a corresponding flow logrecord, for each data packet processed by the public cloud computingenvironment, metadata identifiers comprising a fingerprint identifier oran internet protocol (IP) address, wherein identifying a data packetthat presents a potential security risk comprises determining that thefingerprint identifier or IP address corresponds to a suspected orpreviously detected security risk.
 11. The database system of claim 10,wherein the server is to further: retrieve, from the PCAP recordrepository, a plurality of PCAP records associated with the fingerprintidentifier or the IP address based on flow log records that comprise thefingerprint identifier or the IP address in their respective metadataidentifiers; and transmit the plurality of PCAP records to the computingdevice.
 12. The database system of claim 11, wherein the fingerprintidentifier comprises a JA3 SSL fingerprint.
 13. The database system ofclaim 8, wherein the server is to further: aggregate, based on themetadata identifiers, PCAP records from each virtual machine instance ofthe public cloud computing environment onto one or more hard disks. 14.The database system of claim 8, wherein the PCAP record transmitted tothe computing device corresponds to less than 1% of all PCAP record datastored in the PCAP record repository.
 15. A non-transitorycomputer-readable storage medium having instructions encoded thereonwhich, when executed by a server, cause the server to: generate flow logrecords of network traffic, the flow log records comprising metadataidentifiers descriptive of data packets processed by a public cloudcomputing environment; identify a data packet that presents a potentialsecurity risk based on the metadata identifiers; retrieve a captureddata packet (PCAP) record from a PCAP record repository, the PCAP recordcorresponding to the identified data packet based on the metadataidentifiers descriptive of the data packet; and transmit the PCAP recordto a computing device for network traffic analysis.
 16. Thenon-transitory computer-readable storage medium of claim 15, wherein togenerate the flow log records, the server is to further: store in acorresponding flow log record, for each data packet processed by thepublic cloud computing environment, metadata identifiers comprising anaddress of a corresponding PCAP record of the data packet within thePCAP record repository, wherein the PCAP record is identified within thePCAP record repository based on the address.
 17. The non-transitorycomputer-readable storage medium of claim 15, wherein to generate theflow log records, the server is to further: store in a correspondingflow log record, for each data packet processed by the public cloudcomputing environment, metadata identifiers comprising a fingerprintidentifier or an internet protocol (IP) address, wherein identifying adata packet that presents a potential security risk comprisesdetermining that the fingerprint identifier or IP address corresponds toa suspected or previously detected security risk.
 18. The non-transitorycomputer-readable storage medium of claim 17, wherein the server is tofurther: retrieve, from the PCAP record repository, a plurality of PCAPrecords associated with the fingerprint identifier or the IP addressbased on flow log records that comprise the fingerprint identifier orthe IP address in their respective metadata identifiers; and transmitthe plurality of PCAP records to the computing device.
 19. Thenon-transitory computer-readable storage medium of claim 18, wherein thefingerprint identifier comprises a JA3 SSL fingerprint.
 20. The databasesystem of claim 8, wherein the server is to further: aggregate, based onthe metadata identifiers, PCAP records from each virtual machineinstance of the public cloud computing environment onto one or more harddisks, wherein the aggregated PCAP records correspond to less than 1% ofall PCAP record data stored in the PCAP record repository.